The limits of estimating COVID-19 intervention effects using Bayesian models

Elofsson A, Bryant P

medRxiv - (-) - [2020-11-17; online 2020-08-16]

To limit the rapid spread of COVID-19, most governments have introduced different non-pharmaceutical interventions, which might have severe costs for society. Therefore, it is crucial to evaluate the most cost-effective interventions, using, for instance, Bayesian modelling. Such modelling efforts have deemed lockdown to account for 81% of the reduction in R0, contributing to government policies. Here, we show that these conclusions are unsupported and that policies therefore should not be based on these studies.

Category: Health

Funder: VR

Type: Preprint

DOI 10.1101/2020.08.14.20175240

Crossref 10.1101/2020.08.14.20175240

Publications 7.1.2